mirror of
https://github.com/danny-avila/LibreChat.git
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* 👁️ feat: Add Azure Mistral OCR strategy and endpoint integration This commit introduces a new OCR strategy named 'azure_mistral_ocr', allowing the use of a Mistral OCR endpoint deployed on Azure. The configuration, schemas, and file upload strategies have been updated to support this integration, enabling seamless OCR processing via Azure-hosted Mistral services. * 🗑️ chore: Clean up .gitignore by removing commented-out uncommon directory name * chore: remove unused vars * refactor: Move createAxiosInstance to packages/api/utils and update imports - Removed the createAxiosInstance function from the config module and relocated it to a new utils module for better organization. - Updated import paths in relevant files to reflect the new location of createAxiosInstance. - Added tests for createAxiosInstance to ensure proper functionality and proxy configuration handling. * chore: move axios helpers to packages/api - Added logAxiosError function to @librechat/api for centralized error logging. - Updated imports across various files to use the new logAxiosError function. - Removed the old axios.js utility file as it is no longer needed. * chore: Update Jest moduleNameMapper for improved path resolution - Added a new mapping for '~/' to resolve module paths in Jest configuration, enhancing import handling for the project. * feat: Implement Mistral OCR API integration in TS * chore: Update MistralOCR tests based on new imports * fix: Enhance MistralOCR configuration handling and tests - Introduced helper functions for resolving configuration values from environment variables or hardcoded settings. - Updated the uploadMistralOCR and uploadAzureMistralOCR functions to utilize the new configuration resolution logic. - Improved test cases to ensure correct behavior when mixing environment variables and hardcoded values. - Mocked file upload and signed URL responses in tests to validate functionality without external dependencies. * feat: Enhance MistralOCR functionality with improved configuration and error handling - Introduced helper functions for loading authentication configuration and resolving values from environment variables. - Updated uploadMistralOCR and uploadAzureMistralOCR functions to utilize the new configuration logic. - Added utility functions for processing OCR results and creating error messages. - Improved document type determination and result aggregation for better OCR processing. * refactor: Reorganize OCR type imports in Mistral CRUD file - Moved OCRResult, OCRResultPage, and OCRImage imports to a more logical grouping for better readability and maintainability. * feat: Add file exports to API and create files index * chore: Update OCR types for enhanced structure and clarity - Redesigned OCRImage interface to include mandatory fields and improved naming conventions. - Added PageDimensions interface for better representation of page metrics. - Updated OCRResultPage to include dimensions and mandatory images array. - Refined OCRResult to include document annotation and usage information. * refactor: use TS counterpart of uploadOCR methods * ci: Update MistralOCR tests to reflect new OCR result structure * chore: Bump version of @librechat/api to 1.2.3 in package.json and package-lock.json * chore: Update CONFIG_VERSION to 1.2.8 * chore: remove unused sendEvent function from config module (now imported from '@librechat/api') * chore: remove MistralOCR service files and tests (now in '@librechat/api') * ci: update logger import in ModelService tests to use @librechat/data-schemas --------- Co-authored-by: arthurolivierfortin <arthurolivier.fortin@gmail.com>
221 lines
6.6 KiB
JavaScript
221 lines
6.6 KiB
JavaScript
const axios = require('axios');
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const { logAxiosError } = require('@librechat/api');
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const {
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FileSources,
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VisionModes,
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ImageDetail,
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ContentTypes,
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EModelEndpoint,
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} = require('librechat-data-provider');
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const { getStrategyFunctions } = require('~/server/services/Files/strategies');
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/**
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* Converts a readable stream to a base64 encoded string.
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*
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* @param {NodeJS.ReadableStream} stream - The readable stream to convert.
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* @param {boolean} [destroyStream=true] - Whether to destroy the stream after processing.
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* @returns {Promise<string>} - Promise resolving to the base64 encoded content.
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*/
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async function streamToBase64(stream, destroyStream = true) {
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return new Promise((resolve, reject) => {
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const chunks = [];
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stream.on('data', (chunk) => {
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chunks.push(chunk);
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});
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stream.on('end', () => {
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try {
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const buffer = Buffer.concat(chunks);
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const base64Data = buffer.toString('base64');
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chunks.length = 0; // Clear the array
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resolve(base64Data);
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} catch (err) {
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reject(err);
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}
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});
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stream.on('error', (error) => {
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chunks.length = 0;
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reject(error);
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});
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}).finally(() => {
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// Clean up the stream if required
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if (destroyStream && stream.destroy && typeof stream.destroy === 'function') {
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stream.destroy();
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}
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});
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}
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/**
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* Fetches an image from a URL and returns its base64 representation.
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*
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* @async
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* @param {string} url The URL of the image.
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* @returns {Promise<string>} The base64-encoded string of the image.
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* @throws {Error} If there's an issue fetching the image or encoding it.
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*/
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async function fetchImageToBase64(url) {
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try {
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const response = await axios.get(url, {
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responseType: 'arraybuffer',
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});
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const base64Data = Buffer.from(response.data).toString('base64');
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response.data = null;
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return base64Data;
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} catch (error) {
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const message = 'Error fetching image to convert to base64';
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throw new Error(logAxiosError({ message, error }));
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}
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}
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const base64Only = new Set([
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EModelEndpoint.google,
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EModelEndpoint.anthropic,
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'Ollama',
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'ollama',
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EModelEndpoint.bedrock,
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]);
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const blobStorageSources = new Set([FileSources.azure_blob, FileSources.s3]);
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/**
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* Encodes and formats the given files.
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* @param {Express.Request} req - The request object.
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* @param {Array<MongoFile>} files - The array of files to encode and format.
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* @param {EModelEndpoint} [endpoint] - Optional: The endpoint for the image.
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* @param {string} [mode] - Optional: The endpoint mode for the image.
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* @returns {Promise<{ text: string; files: MongoFile[]; image_urls: MessageContentImageUrl[] }>} - A promise that resolves to the result object containing the encoded images and file details.
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*/
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async function encodeAndFormat(req, files, endpoint, mode) {
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const promises = [];
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/** @type {Record<FileSources, Pick<ReturnType<typeof getStrategyFunctions>, 'prepareImagePayload' | 'getDownloadStream'>>} */
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const encodingMethods = {};
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/** @type {{ text: string; files: MongoFile[]; image_urls: MessageContentImageUrl[] }} */
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const result = {
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text: '',
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files: [],
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image_urls: [],
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};
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if (!files || !files.length) {
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return result;
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}
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for (let file of files) {
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/** @type {FileSources} */
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const source = file.source ?? FileSources.local;
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if (source === FileSources.text && file.text) {
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result.text += `${!result.text ? 'Attached document(s):\n```md' : '\n\n---\n\n'}# "${file.filename}"\n${file.text}\n`;
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}
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if (!file.height) {
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promises.push([file, null]);
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continue;
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}
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if (!encodingMethods[source]) {
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const { prepareImagePayload, getDownloadStream } = getStrategyFunctions(source);
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if (!prepareImagePayload) {
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throw new Error(`Encoding function not implemented for ${source}`);
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}
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encodingMethods[source] = { prepareImagePayload, getDownloadStream };
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}
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const preparePayload = encodingMethods[source].prepareImagePayload;
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/* We need to fetch the image and convert it to base64 if we are using S3/Azure Blob storage. */
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if (blobStorageSources.has(source)) {
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try {
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const downloadStream = encodingMethods[source].getDownloadStream;
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let stream = await downloadStream(req, file.filepath);
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let base64Data = await streamToBase64(stream);
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stream = null;
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promises.push([file, base64Data]);
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base64Data = null;
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continue;
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} catch (error) {
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// Error handling code
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}
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} else if (source !== FileSources.local && base64Only.has(endpoint)) {
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const [_file, imageURL] = await preparePayload(req, file);
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promises.push([_file, await fetchImageToBase64(imageURL)]);
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continue;
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}
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promises.push(preparePayload(req, file));
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}
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if (result.text) {
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result.text += '\n```';
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}
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const detail = req.body.imageDetail ?? ImageDetail.auto;
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/** @type {Array<[MongoFile, string]>} */
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const formattedImages = await Promise.all(promises);
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promises.length = 0;
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for (const [file, imageContent] of formattedImages) {
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const fileMetadata = {
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type: file.type,
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file_id: file.file_id,
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filepath: file.filepath,
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filename: file.filename,
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embedded: !!file.embedded,
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metadata: file.metadata,
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};
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if (file.height && file.width) {
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fileMetadata.height = file.height;
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fileMetadata.width = file.width;
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}
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if (!imageContent) {
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result.files.push(fileMetadata);
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continue;
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}
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const imagePart = {
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type: ContentTypes.IMAGE_URL,
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image_url: {
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url: imageContent.startsWith('http')
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? imageContent
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: `data:${file.type};base64,${imageContent}`,
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detail,
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},
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};
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if (mode === VisionModes.agents) {
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result.image_urls.push({ ...imagePart });
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result.files.push({ ...fileMetadata });
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continue;
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}
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if (endpoint && endpoint === EModelEndpoint.google && mode === VisionModes.generative) {
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delete imagePart.image_url;
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imagePart.inlineData = {
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mimeType: file.type,
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data: imageContent,
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};
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} else if (endpoint && endpoint === EModelEndpoint.google) {
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imagePart.image_url = imagePart.image_url.url;
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} else if (endpoint && endpoint === EModelEndpoint.anthropic) {
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imagePart.type = 'image';
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imagePart.source = {
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type: 'base64',
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media_type: file.type,
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data: imageContent,
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};
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delete imagePart.image_url;
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}
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result.image_urls.push({ ...imagePart });
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result.files.push({ ...fileMetadata });
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}
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formattedImages.length = 0;
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return { ...result };
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}
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module.exports = {
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encodeAndFormat,
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};
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